This paper presents an adaptive feedback linearization control scheme for induction motors using stator fluxes. By using stator flukes as states, overparameterization is prevented and control inputs can be determined straightforwardly unlike in existing schemes. This approach leads to the decrease of the relative degree for the flux modulus and thus yields a simpler control algorithm than the prior results. In this paper. adaptation schemes are suggested to compensate for the variations of stator resistance. rotor resistance and load torque. In particular, the adaptation to the variation of stator resistance with a feedback linearization control is a new trial. In addition, to improve the convergence of rotor resistance estimation, the differences between stator currents and its estimates are used for the parameter adaptation. The simulations show that torque and flux are controlled independently and that the estimates of stator resistance, rotor resistance, and load torque converge to their true values. Actual experiments on a 3.7㎾ induction motor verify the effectiveness of the proposed method.

In this paper, Η$_{\infty}$ depth and course controller of an AUV(Autonomous Underwater Vehicle) using Η$_{\infty}$ servo control is proposed. The Η$_{\infty}$ servo problem is formulated to design the controllers satisfying a robust tracking property with modeling errors and disturbances. The solution of the Η$_{\infty}$ servo problem is as fellows: first, this problem is modified as an Η$_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The Η$_{\infty}$ depth and course controller are designed to satisfy with the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under disturbances(wave force, wave moment, tide). The performances of the designed controllers are evaluated with computer simulations, and finally these simulation results show the usefulness and application of the proposed Η$_{\infty}$ depth and course control system.

An integrated robust fault diagnosis and fault accommodation strategy for a class of linear stochastic systems subjected to unknown disturbances is presented under the assumption that only a single fault may occur at a given time. The strategy is based on the fault isolation and estimation using a bank of robust two-stage Kalman filters and introduction of the additive compensation input for cancelling out the fault's effect on the system. Each filter is set up such that the residual is decoupled from unknown disturbances and fault with the influence vector designed in the filter. Simulation results for the simplified longitudinal flight control system with parameter uncertainties, process and sensor noises demonstrate the effectiveness of the present approach.

This paper proposes a nonlinear adaptive controller based on back-stepping method for tracking reference substrate concentration by manipulating dilution rate in a continuous baker's yeast cultivating process in stirred tank bioreactor. Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The Haldane model for the specific growth rate depending on only substrate concentration is used in this paper. Due to the uncertainty of specific growth rate, it has been modified as a function including the unknown parameter with known bounded values. The substrate concentration in the bioreactor and feed line are measured. The deviation from the reference is observed when the external disturbance such as the change of the feed is introduced to the system. The effectiveness of the proposed controller is shown through simulation results in continuous system.

This paper has shown that the impulse and the unit step responses of 2nd-order systems can be computed by an analytic method. Three different 2nd-order systems are investigated: the prototype system, the system with one LHP(left half plane) real zero and the system with one RHP(right half plane) real zero. It has also shown that the effects of the LHP or the RHP zero are very serious when the zero is getting closer to the origin on the complex plane. Based on these analytic results, this paper has presented two sufficient and necessary conditions for 2nd-order linear SISO(single-input/single-output) stable systems to have the nonovershooting and the monotone nondecreasing step response, respectively. The latter condition can be extended to the sufficient conditions for the monotone nondecreasing step response of high-order systems.

In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.

A position tracking control schemes on the precise mechanical system in presence of nonlinear dynamic friction is proposed. A nonlinear dynamic friction is regarded as the bristle friction model to compensate effects of friction. The conventional sliding mode controller often has been used as a non-model-based friction controller, but it has a poor tracking performance in high-precision position tracking application since it completely cannot compensate the friction effect below a certain precision level. Thus to improve the precise position tracking performance, we propose the sliding mode control method combined with the friction-model-based observer having tunable structure of the transient response. Then this control scheme has a good transient response as well as the high precise tracking performance compared with the conventional sliding mode control without observer and the control system with similar type of observer. The experiments on the bali-screw drive table with the nonlinear dynamic friction show the feasibility of the proposed control scheme.

The measured rate of the tracking sensor becomes biased under some operational situation. For a highly maneuverable aircraft in 3D space, the target dynamics changes from time to time, and the Kalman filter using position measurement only can not be used effectively to reject the rate measurement bias error. To cope with this problem, we present a new algorithm which incorporate FIR-type filter and FIR-type fixed-lag smoother, and demonstrate that it has the optimal performance in terms of both estimation accuracy and response time through an application example to the anti-aircraft gun fire control system(AAGFCS).

Two adaptive nonlinear friction compensation schemes are proposed for second-order nonlinear mechanical systems with a partially known nonlinear dynamic friction model to achieve asymptotic position and velocity tracking. The first scheme has auxiliary filtered states so that a simple open-loop observer can be used. The second one has a dual-observer structure to estimate two different nonlinear aspects of the friction state. Conditions for the parameter estimates to converge to the true parameter values are presented. Simulation results are utilized to show control performance and to demonstrate the convergence of the parameter estimates to their true values.

In this paper, we consider the track-following control problem in the optical data storage systems in the presence of the eccentricity. The eccentricity results in the radial deviation of the objective lens so that it degrades the reliability of the data decoding system. To cope with the eccentricity, an adaptive disturbance compensation technique is newly proposed in the time domain based on a disturbance observer of reduced order, which effectively estimates the low frequency components of the disturbance. The proposed compensator is simply added to the conventional feedback control. The error dynamics of the observer and the sensitivity analysis are given to illustrate the effectiveness of the proposed approach. Finally, through experiments in an optical storage system, the feasibility of the proposed approach is verified.

In this paper, the guaranteed cost filtering design method for linear time delay systems with convex bounded uncertainties in discrete-time case is presented. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytotype less conservative than norm bounded parameter uncertainty. The main purpose is to design a stable filter which minimizes the guaranteed cost. The sufficient condition for the existence of filter, the guaranteed cost filter design method, and the upper bound of the guaranteed cost are proposed. Since the proposed sufficient conditions are LMI(linear matrix inequality) forms in terms of all finding variables, all solutions can be obtained simultaneously by means of powerful convex programming tools with global convergence assured. Finally, a numerical example is given to check the validity of the proposed method.

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

When a construction company builds a high structure. many piles should be driven into the ground by a hammer whose weight is 7,000 kg in order to make the ground under the structure safe and strong. So. it is essential to determine whether a pile is penetrated into the ground enough to support the weight of the structure since ground characteristics at different locations are different each other. This paper proposes a visual measurement system for pile rebound and penetration movement including vibration using a high-speed line-scan camera and a specially designed mark to recognize two-dimensional motion parameters of the mark using only a line-scan camera. A mark stacking white and black right-angled triangles is used for the measurement, and movement information for vertical distance, horizontal distance and rotational angle is determined simultaneously. Especially- by adopting a line-scan CCD camera whose line rate is 20 ㎑. the measurement performance of dynamic characteristics of the pile at impact instant is improved dramatically.

Obstacle avoidance of underactuated robot manipulators using switching computed torque method (SCTM) is presented. One fundamental feature of this novel method is to use partly stable controllers (PSCs) in order to fulfill the ultimate control objective. Here, we use genetic algorithms (GAs) to acquire the optimum switching sequence of the control actions for a given time frame with the available set of elemental controllers, depending on which links/variables are controlled. The effectiveness of the concept is illustrated by taking a three-degrees-of-freedom (DOF) manipulator and showing enhanced performance of the proposed control methodology.

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.